Literature DB >> 16049378

Identification of schizophrenic patients by examination of body odor using gas chromatography-mass spectrometry and a cross-selective gas sensor array.

Corrado Di Natale1, Roberto Paolesse, Giuseppe D'Arcangelo, Paolo Comandini, Giorgio Pennazza, Eugenio Martinelli, Santo Rullo, Maria Claudia Roscioni, Claudio Roscioni, Alessandro Finazzi-Agrò, Arnaldo D'Amico.   

Abstract

BACKGROUND: Previous findings have shown that the body odor of patients affected by schizophrenia contains some specific compounds. Chemical sensor technology has proved to be able to classify different odours. We investigated the possibility of using a chemical sensor array to detect body odor alteration in schizophrenic patients. MATERIAL/
METHODS: The sweat of subjects was sampled and analysed by Gas Chromatography-Mass Spectrometry (GC-MS) and by an array of cross-selective gas sensors. A total of 27 individuals were involved in the experiment: 9 schizophrenics, 9 with other mental disorders, and 9 controls.
RESULTS: GC-MS analysis showed a richer composition for the sweat of schizophrenic patients. Nevertheless, the individuation of specific markers was unsuccessful. On the other hand, statistical analysis of cross-selective gas sensor data provided a complete classification of schizophrenic patients with respect to the other three groups.
CONCLUSIONS: The alteration of body odor in schizophrenic patients was confirmed by GC-MS and chemical sensor array. Results show that the alteration is complex and cannot be limited to a single compound, but rather to a global variation of the body odor.

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Year:  2005        PMID: 16049378

Source DB:  PubMed          Journal:  Med Sci Monit        ISSN: 1234-1010


  3 in total

1.  Design and test of a biosensor-based multisensorial system: a proof of concept study.

Authors:  Marco Santonico; Giorgio Pennazza; Simone Grasso; Arnaldo D'Amico; Mariano Bizzarri
Journal:  Sensors (Basel)       Date:  2013-12-04       Impact factor: 3.576

2.  Detecting cannabis use on the human skin surface via an electronic nose system.

Authors:  Andreas Voss; Katharina Witt; Tobias Kaschowitz; Wolf Poitz; Andreas Ebert; Patrik Roser; Karl-Jürgen Bär
Journal:  Sensors (Basel)       Date:  2014-07-23       Impact factor: 3.576

3.  Machine Learning Analysis of Electronic Nose in a Transdiagnostic Community Sample With a Streamlined Data Collection Approach: No Links Between Volatile Organic Compounds and Psychiatric Symptoms.

Authors:  Bohan Xu; Mahdi Moradi; Rayus Kuplicki; Jennifer L Stewart; Brett McKinney; Sandip Sen; Martin P Paulus
Journal:  Front Psychiatry       Date:  2020-09-16       Impact factor: 4.157

  3 in total

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